mapstitch.cpp

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#include "mapstitch/mapstitch.h"
#include "math.h"

StitchedMap::StitchedMap(Mat &img1, Mat &img2, float max_pairwise_distance)
{
  // load images, TODO: check that they're grayscale
  image1 = img1.clone();
  image2 = img2.clone();

  // create feature detector set.
  OrbFeatureDetector detector;
  OrbDescriptorExtractor dexc;
  BFMatcher dematc(NORM_HAMMING, false);

  // 1. extract keypoints
  detector.detect(image1, kpv1);
  detector.detect(image2, kpv2);

  // 2. extract descriptors
  dexc.compute(image1, kpv1, dscv1);
  dexc.compute(image2, kpv2, dscv2);

  // 3. match keypoints
  dematc.match(dscv1, dscv2, matches);

  // 4. find matching point pairs with same distance in both images
  for (size_t i=0; i<matches.size(); i++) {
    KeyPoint a1 = kpv1[matches[i].queryIdx],
             b1 = kpv2[matches[i].trainIdx];

    if (matches[i].distance > 30)
      continue;

    for (size_t j=0; j<matches.size(); j++) {
      KeyPoint a2 = kpv1[matches[j].queryIdx],
               b2 = kpv2[matches[j].trainIdx];

      if (matches[j].distance > 30)
        continue;

      if ( fabs(norm(a1.pt-a2.pt) - norm(b1.pt-b2.pt)) > max_pairwise_distance ||
           fabs(norm(a1.pt-a2.pt) - norm(b1.pt-b2.pt)) == 0)
        continue;

      coord1.push_back(a1.pt);
      coord1.push_back(a2.pt);
      coord2.push_back(b1.pt);
      coord2.push_back(b2.pt);

      fil1.push_back(a1);
      fil1.push_back(a2);
      fil2.push_back(b1);
      fil2.push_back(b2);
    }
  }

  if (coord1.size() == 0)
    ;

  // 5. find homography
  H = estimateRigidTransform(coord2, coord1, false);

  // 6. calculate this stuff for information
  rotation = 180./M_PI*atan2(H.at<double>(0,1),H.at<double>(1,1)),
  transx   = H.at<double>(0,2),
  transy   = H.at<double>(1,2);
  scalex   = sqrt(pow(H.at<double>(0,0),2)+pow(H.at<double>(0,1),2));
  scaley   = sqrt(pow(H.at<double>(1,0),2)+pow(H.at<double>(1,1),2));
}

Mat
StitchedMap::get_debug()
{
  Mat out;
  drawKeypoints(image1, kpv1, image1, Scalar(255,0,0));
  drawKeypoints(image2, kpv2, image2, Scalar(255,0,0));
  drawMatches(image1,fil1, image2,fil2, matches,out,Scalar::all(-1),Scalar::all(-1));
  return out;
}

Mat // return the stitched maps
StitchedMap::get_stitch()
{
  // create storage for new image and get transformations
  Mat image(image2.size(), image2.type());
  warpAffine(image2,image,H,image.size());

  // blend image1 onto the transformed image2
  addWeighted(image,.5,image1,.5,0.0,image);

  return image;
}

StitchedMap::~StitchedMap() { }